def test_ifu_no_background():
"""Test 3"""
# There is a background ...
input = make_ifu_cube(data_shape, source=5., background=3.7,
x_center=x_center, y_center=y_center,
radius=radius,
inner_bkg=inner_bkg, outer_bkg=outer_bkg)
# ... but turn off background subtraction anyway.
ref_image_2d = make_ref_image(data_shape[-2:], # 2-D ref image
x_center=x_center, y_center=y_center,
radius=radius,
inner_bkg=None, outer_bkg=None)
# Create a reference dictionary to specify the extraction parameters.
# This will serve as the "truth" for comparison with the results of
# using a reference image.
ref_dict = {"ref_file_type": extract.FILE_TYPE_JSON,
"apertures": [{"id": "ANY",
"x_center": x_center,
"y_center": y_center,
"radius": radius,
"subtract_background": True,
"method": method
}
]
}
# Set background subtraction to False, overriding what was specified
# in the reference dictionary.
truth = extract.do_extract1d(input, ref_dict, smoothing_length=0,
bkg_order=0, log_increment=50,
subtract_background=False)
ref_dict_2d = {"ref_file_type": extract.FILE_TYPE_IMAGE,
"ref_model": ref_image_2d}
output = extract.do_extract1d(input, ref_dict_2d, smoothing_length=0,
bkg_order=0, log_increment=50,
subtract_background=False)
true_wl = truth.spec[0].spec_table['wavelength']
true_flux = truth.spec[0].spec_table['flux']
true_bkg = truth.spec[0].spec_table['background']
wavelength = output.spec[0].spec_table['wavelength']
flux = output.spec[0].spec_table['flux']
background = output.spec[0].spec_table['background']
assert np.allclose(wavelength, true_wl, rtol=1.e-14, atol=1.e-14)
assert np.allclose(flux, true_flux, atol=150.)
assert np.allclose(background, true_bkg, atol=1.)
input.close()
truth.close()
output.close()
del ref_dict_2d
ref_image_2d.close()
def test_ifu_3d():
"""Test 2"""
input = make_ifu_cube(data_shape, source=5., background=3.7,
x_center=x_center, y_center=y_center,
radius=radius,
inner_bkg=inner_bkg, outer_bkg=outer_bkg)
ref_image_2d = make_ref_image(data_shape[-2:], # 2-D ref image
x_center=x_center, y_center=y_center,
radius=radius,
inner_bkg=inner_bkg, outer_bkg=outer_bkg)
ref_image_3d = make_ref_image(data_shape, # 3-D ref image
x_center=x_center, y_center=y_center,
radius=radius,
inner_bkg=inner_bkg, outer_bkg=outer_bkg)
ref_dict_2d = {"ref_file_type": extract.FILE_TYPE_IMAGE,
"ref_model": ref_image_2d}
truth = extract.do_extract1d(input, ref_dict_2d, smoothing_length=0,
bkg_order=0, log_increment=50,
subtract_background=True)
ref_dict_3d = {"ref_file_type": extract.FILE_TYPE_IMAGE,
"ref_model": ref_image_3d}
output = extract.do_extract1d(input, ref_dict_3d, smoothing_length=0,
bkg_order=0, log_increment=50,
subtract_background=True)
true_wl = truth.spec[0].spec_table['wavelength']
true_flux = truth.spec[0].spec_table['flux']
true_bkg = truth.spec[0].spec_table['background']
wavelength = output.spec[0].spec_table['wavelength']
flux = output.spec[0].spec_table['flux']
background = output.spec[0].spec_table['background']
# These should all be the same because the reference image is the
# same in every plane.
assert np.allclose(wavelength, true_wl, rtol=1.e-14, atol=1.e-14)
assert np.allclose(flux, true_flux, atol=1.e-14)
assert np.allclose(background, true_bkg, atol=1.e-14)
input.close()
truth.close()
output.close()
del ref_dict_2d, ref_dict_3d
ref_image_2d.close()
ref_image_3d.close()
def test_ifu_2d():
"""Test 1"""
input = make_ifu_cube(data_shape,
source=5.,
background=3.7,
x_center=x_center,
y_center=y_center,
radius=radius,
inner_bkg=inner_bkg,
outer_bkg=outer_bkg)
ref_image_2d = make_ref_image(
data_shape[-2:], # 2-D ref image
x_center=x_center,
y_center=y_center,
radius=radius,
inner_bkg=inner_bkg,
outer_bkg=outer_bkg)
# Create a reference dictionary to specify the extraction parameters.
# This will serve as the "truth" for comparison with the results of
# using a reference image.
ref_dict = {
"ref_file_type":
extract.FILE_TYPE_JSON,
"apertures": [{
"id": "ANY",
"x_center": x_center,
"y_center": y_center,
"radius": radius,
"subtract_background": True,
"inner_bkg": inner_bkg,
"outer_bkg": outer_bkg,
"method": method
}]
}
truth = extract.do_extract1d(input,
ref_dict,
smoothing_length=0,
bkg_order=0,
log_increment=50,
subtract_background=True)
ref_dict_2d = {
"ref_file_type": extract.FILE_TYPE_IMAGE,
"ref_model": ref_image_2d
}
output = extract.do_extract1d(input,
ref_dict_2d,
smoothing_length=0,
bkg_order=0,
log_increment=50,
subtract_background=True)
true_wl = truth.spec[0].spec_table['wavelength']
true_flux = truth.spec[0].spec_table['flux']
true_bkg = truth.spec[0].spec_table['background']
wavelength = output.spec[0].spec_table['wavelength']
flux = output.spec[0].spec_table['flux']
background = output.spec[0].spec_table['background']
"""The wavelengths should agree exactly, because they were computed
in the same way for both `output` and `truth`.
The source is 5 per pixel, and since the radius is 11.5, the sum of
all those values is 2077.378; this is the flux (actually net, but net
was moved to flux). The IFU cube was made by assigning values to the
nearest pixels, however, resulting in jagged edges to the disk and
background annulus. With a radius of 11.5 (circumference = 72.26) and
outer background radius of 16.5 (circumference = 103.67), differences
of order 150 between an exact computation and nearest pixel are not
unreasonable.
"""
assert np.allclose(wavelength, true_wl, rtol=1.e-14, atol=1.e-14)
assert np.allclose(flux, true_flux, rtol=0.05)
assert np.allclose(background, true_bkg, rtol=0.1)
input.close()
truth.close()
output.close()
del ref_dict_2d
ref_image_2d.close()
def test_ifu_2d():
"""Test 1"""
input = make_ifu_cube(data_shape, source=5., background=3.7,
x_center=x_center, y_center=y_center,
radius=radius,
inner_bkg=inner_bkg, outer_bkg=outer_bkg)
ref_image_2d = make_ref_image(data_shape[-2:], # 2-D ref image
x_center=x_center, y_center=y_center,
radius=radius,
inner_bkg=inner_bkg, outer_bkg=outer_bkg)
# Create a reference dictionary to specify the extraction parameters.
# This will serve as the "truth" for comparison with the results of
# using a reference image.
ref_dict = {"ref_file_type": extract.FILE_TYPE_JSON,
"apertures": [{"id": "ANY",
"x_center": x_center,
"y_center": y_center,
"radius": radius,
"subtract_background": True,
"inner_bkg": inner_bkg,
"outer_bkg": outer_bkg,
"method": method
}
]
}
truth = extract.do_extract1d(input, ref_dict, smoothing_length=0,
bkg_order=0, log_increment=50,
subtract_background=True)
ref_dict_2d = {"ref_file_type": extract.FILE_TYPE_IMAGE,
"ref_model": ref_image_2d}
output = extract.do_extract1d(input, ref_dict_2d, smoothing_length=0,
bkg_order=0, log_increment=50,
subtract_background=True)
true_wl = truth.spec[0].spec_table['wavelength']
true_flux = truth.spec[0].spec_table['flux']
true_bkg = truth.spec[0].spec_table['background']
wavelength = output.spec[0].spec_table['wavelength']
flux = output.spec[0].spec_table['flux']
background = output.spec[0].spec_table['background']
"""The wavelengths should agree exactly, because they were computed
in the same way for both `output` and `truth`.
The source is 5 per pixel, and since the radius is 11.5, the sum of
all those values is 2077.378; this is the flux (actually net, but net
was moved to flux). The IFU cube was made by assigning values to the
nearest pixels, however, resulting in jagged edges to the disk and
background annulus. With a radius of 11.5 (circumference = 72.26) and
outer background radius of 16.5 (circumference = 103.67), differences
of order 150 between an exact computation and nearest pixel are not
unreasonable.
"""
assert np.allclose(wavelength, true_wl, rtol=1.e-14, atol=1.e-14)
assert np.allclose(flux, true_flux, atol=150.)
assert np.allclose(background, true_bkg, atol=150.)
input.close()
truth.close()
output.close()
del ref_dict_2d
ref_image_2d.close()
